Low back pain (LBP) affects more than one third of the population at any given time, and chronic LBP is responsible for increased medical costs, functional limitations and decreased quality of life. A clear etiology is often difficult to identify, but aberrant posture and movement are considered contributing factors to chronic LBP that are addressed during physiotherapy intervention. Information about aberrant movement during functional activities in people with LBP can help inform more effective interventions. The purpose of this study was to determine if there are differences in lumbar spine and lower extremity kinematics in people with and without LBP during a step-up task. A convenience sample of 37 participants included 19 with LBP and 18 without a history of LBP. All participants were between the ages of 18 and 65, and controls were matched to participants with LBP based on age, gender and BMI. A motion capture system was used to record spine and lower extremity kinematics during the step-up task. ANOVA tests were used to determine differences in three-dimensional kinematics between groups. Participants with LBP displayed less lower lumbar motion in the sagittal plane (P = 0.001), more knee motion in the coronal plane (P = 0.001), and more lower extremity motion in the axial plane (P = 0.002) than controls. People with LBP display less lower lumbar spine motion in the sagittal plane and more out-of-plane lower extremity motion. Clinically, the step-up task can be used to identify these aberrant movements to develop more focused functional interventions for patients with LBP. Not applicable.

Spine movement is a daily activity that can indicate health status changes, including low back pain (LBP) problems. Repetitious and continuous movement on the spine and incorrect postures during daily functional activities may lead to the potential development and persistence of LBP problems. Therefore, monitoring of posture and movement is essential when designing LBP interventions. Typically, LBP diagnosis is facilitated by monitoring upper body posture and movement impairments, particularly during functional activities using body motion sensors. This study presents a fully wireless multi-sensor cluster system to monitor spine movements. The study suggests an attempt to develop a new method to monitor the lumbopelvic movements of interest selectively. In addition, the research employs a custom-designed robotic lumbar spine simulator to generate the ideal lumbopelvic posture and movements for reference sensor data. The mechanical motion templates provide an automated sensor pattern recognition mechanism for diagnosing the LBP.